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The impact and response to electronic bullying and traditional bullying among adolescents
Computers in Human Behavior 49 (2015) 288–295
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Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
The impact and response to electronic bullying and traditional bullying among adolescents Stacy Horner a, Yvonne Asher b, Gary D. Fireman b,⇑ a b
Metrowest Neuropsychology, Westborough, MA, United States Department of Psychology, Suffolk University, United States
a r t i c l e
i n f o
Article history:
Keywords: Peer victimization Electronic bullying Adolescence
a b s t r a c t With adolescents’ frequent use of social media, electronic bullying has emerged as a powerful platform for peer victimization. The present two studies explore how adolescents perceive electronic vs. traditional bullying in emotional impact and strategic responses. In Study 1, 97 adolescents (mean age = 15) viewed hypothetical peer victimization scenarios, in parallel electronic and traditional forms, with female characters experiencing indirect relational aggression and direct verbal aggression. In Study 2, 47 adolescents (mean age = 14) viewed the direct verbal aggression scenario from Study 1, and a new scenario, involving male characters in the context of direct verbal aggression. Participants were asked to imagine themselves as the victim in all scenarios and then rate their emotional reactions, strategic responses, and goals for the outcome. Adolescents reported significant negative emotions and disruptions in typical daily activities as the victim across divergent bullying scenarios. In both studies few differences emerged when comparing electronic to traditional bullying, suggesting that online and off-line bullying are subtypes of peer victimization. There were expected differences in strategic responses that fit the medium of the bullying. Results also suggested that embarrassment is a common and highly relevant negative experience in both indirect relational and direct verbal aggression among adolescents. Ó 2015 Published by Elsevier Ltd.
1. Introduction Concern about school based bullying has recently grown to include peer aggression that occurs through social media. With the dramatic increase in adolescents’ use of social media and the time spent in unsupervised interaction on social media, there is a concurrent rise in opportunity for bullying within this medium. Prior to the rise of social media, bullying was typically conceptualized as the result of an exchange between at least two people, a bully and a victim, in direct face-to-face contact with each other. Given the scope of bullying and the potential damage to healthy development, the Center for Disease Control and Prevention and the Department of Education have recognized it as a significant public health concern. The CDC has provided a uniform definition to support effective scholarship, prevention and intervention: Any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners
⇑ Corresponding author at: Department of Psychology, Suffolk University, Boston, MA 02114, United States. E-mail address: gfi[email protected] (G.D. Fireman). http://dx.doi.org/10.1016/j.chb.2015.03.007 0747-5632/Ó 2015 Published by Elsevier Ltd.
that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated. Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm (Gladden, Vivolo-Kantor, Hamburger, & Lumpkin, 2014, p. 7). Bullying that occurs through social media popularly referred to as ‘‘cyberbullying’’ is labeled ‘‘electronic bullying’’ by the CDC. Social media is an often-used form of interaction among adolescents with 95% of 12–17 year olds reporting utilization of the Internet (Lenhart et al., 2011). It should be noted that in electronic bullying the unwanted aggressive behavior may be perceived by the victim as repeated not due to repeated acts of the bully but rather, due to the enduring nature of electronic content with repeated viewings and potential for being shared widely. Given the distinct qualities of electronic bullying, questions arise regarding the nature and intensity of emotional and strategic responses of youth to electronic vs. traditional bullying. Being a victim of traditional bullying is connected to a number of negative academic, social, and psychological consequences (e.g., Nansel et al., 2001; Rigby & Slee, 1991). Similar negative consequences have been reported through survey research for victims
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of electronic bullying, including school avoidance, truancy, eating disorders, depression, poor self-esteem, and suicidal ideation or suicide (e.g., Schneider, O’Donnell, Stueve, & Coulter, 2012). However, despite the tragic examples of electronic bullying reflected in the media, little experimental research distinguishing electronic bullying from traditional bullying has been completed (for exceptions, see Pieschl, Porsch, Kahl, & Klockenbusch, 2013; Sticca & Perren, 2013). The present research is one of a few initial efforts to move beyond correlational and retrospective designs by providing adolescents with specific hypothetical scenarios in order to examine how adolescents conceptualize and strategize about bullying and electronic bullying. The negative behaviors involved in bullying are often identified as direct, including overtly aggressive behaviors such as physical acts (e.g., pushing, punching) and verbal acts (e.g., insults, teasing), or indirect, which includes relationally aggressive acts designed to damage social relationships (e.g., spreading rumors, social exclusion). Similar to traditional bullying, most electronic bullying requires an intentional act committed by an individual or group in order to cause harm or distress to another individual or group but done through electronic communication technologies (Beran & Li, 2005; Mason, 2008). In one recent study, respondents were asked about different types of electronic bullying they were exposed to (Aricak et al., 2008) with 19% reporting threats while 81% reported some form of embarrassment (e.g., teasing, insults, rumors, or pictures displayed by others without consent). Although electronic bullying also requires a power differential between the bully and the victim (Mason, 2008), across online and off-line contexts the source of a bully’s strength and the reasons why a victim feels defenseless may vary considerably. As opposed to traditional bullying in which bullies often rely on a combination of attractiveness, local popularity, and physical strength as a source of power, it has been hypothesized that in electronic bullying the power is based more exclusively on a bully’s social connectedness and prestige all of which are visible on social networking site profiles (Patchin & Hinduja, 2006). For adolescents, who are especially concerned about what others think of them and are more likely to believe others are always watching (Elkind, 1967), electronic bullying that interrupts relationships, can be seen by many, and remains visible over time may be particularly upsetting. In the present research, the social media of Facebook was approximated and the numbers of ‘‘liked’’, tagged photos, and ‘‘friends’’ were all considered with the bully appearing more popular than the victim. As with traditional bullying, a number of negative consequences have been associated with electronic bullying. Self-report data indicate that adolescents who are victims of electronic bulling experience a number of emotional consequences (e.g., feelings of sadness, depression, anxiety, fear), as well as behavioral difficulties (e.g., missing school, difficulty concentrating, losing trust in peers, and falling grades; Beran & Li, 2005; Dehue, Bolman, & Völlink, 2008; Raskauskas & Stoltz, 2007) that are similar to traditional bullying (Bauman & Newman, 2013). Utilizing a retrospective self-report methodology with college students, Bauman and Newman (2013) found that perceived distress at a bullying situation was not consistently related to the form of bullying (i.e., electronic or traditional), but rather related to the factors involved in the specific situation. Similarly, Sticca and Perren (2013) note that ‘‘cyberbullying is not a priori perceived as worse than traditional bullying’’ (p. 739), but that certain factors (e.g., publicity of the bullying) determine adolescents’ perceived level of distress. Therefore, the present two studies examine adolescents’ emotional and strategic responses to bullying in distinct online and off-line scenarios. In a large self-report study, 1852 adolescents between the ages of 4 and 19 who had been bullied participated in an online survey about responses to traditional bullying (Craig, Pepler, & Blais,
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2007). Youth were presented with 12 possible strategies to cope with peer victimization (e.g., telling parents, telling other students, standing up to the bully, distraction, ignoring bullying), and asked to endorse which strategies they had utilized. The most frequent response, endorsed by approximately 50% of the respondents, was that they had tried to ignore the bullying. Smith et al. (2008) utilized large-scale surveys and focus groups to assess 11–16 year-olds’ beliefs regarding the best ways to stop electronic bullying. When provided with a list of possible ways to cope with electronic bullying, the most commonly endorsed strategies were to block messages/identities (75%), tell someone (63%), change email address/phone number (57%), and ignoring the behavior (41%). In traditional bullying prevention programs, telling an adult is often a recommended strategy. However, there is evidence to suggest that traditional victims are more likely to tell others than victims of electronic bullying (Smith et al., 2008). In research examining who victims tell about electronic bullying, the most frequent responses are to tell ‘‘no one’’ or ‘‘friends’’, with parents and teachers reported far less often (Aricak et al., 2008; Dehue et al., 2008; National Children’s Home, 2005; Slonje & Smith, 2008). It is possible that adolescents are more willing to tell friends (as opposed to parents or teachers) about both electronic and traditional bullying, as friends are an important source of social and emotional support during this developmental period. In addition, a substantial number of adolescents do not think school staff would or could do anything to stop electronic bullying (47%). These findings highlight the need to better understand if adolescents would respond differently to comparable bullying situations across off-line and online contexts in order to provide parents and professionals with guidance on how best to help those being bullied.
2. The present studies The present two studies build on the existing research by examining 9th and 10th grade adolescents’ perceptions of the impact and ways to respond to electronic bullying vs. traditional bullying. As mentioned above, the majority of research to date has used self-report survey methodologies, which have notable limitations (Raskauskas & Stoltz, 2007). The current research uses a design that allows adolescents to respond to specific hypothetical scenarios one focused on a situation involving threat of overt aggression (OA), and the other focused on a situation involving relational aggression (RA). These were chosen as prior research has suggested that threat of OA and RA (specifically, embarrassment) situations are the most commonly experienced types of bullying for adolescents (e.g., Aricak et al., 2008; Huang & Chou, 2010; Lenhart, 2007). Adolescents viewed the same scenarios in both traditional and online formats to make direct comparisons possible. Since December 2007, Facebook has become one of the most frequently used social networking sites (Smith, 2009b). Because of Facebook’s popularity among adolescents, the present research was designed to mimic this social networking site. The present research is divided into two distinct studies: the first study examined male and female adolescents’ responses to two scenarios, OA and RA, with female characters only. The second study replicates the OA scenario and adds the examination of male and female adolescents’ responses to an OA scenario with male characters (as opposed to female characters). Analyses focus on adolescents’ ratings of their emotional reactions and problem solving strategies in response to the bullying scenarios. We hypothesize that the bullying scenarios involving OA will elicit more negative emotion and distinct strategies in traditional vs. electronic platforms. In contrast, with RA, we hypothesize a more negative emotional impact online. We also predict that males will be more distressed by the OA bullying scenarios and females by the RA scenarios.
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3. Study 1 3.1. Methods 3.1.1. Participants Adolescents were selected from a large public high school near a major Northeast city. Adolescents were recruited through announcements in their study hall classrooms and via email. A total of 97 students, of approximately 450 eligible students, had parental consent, provided assent, and completed the study. Adolescents’ responses were first examined to ensure they were attending to the stimuli and identified the correct person as the victim of bullying. Eight students were not used in the following analysis (n = 89) because they failed to identify the correct victim. Adolescents were asked to provide demographic information, summarized in Table 1. 3.1.2. Development of stimuli The selection of specific scenarios was based on two key factors: representativeness of typical bullying experiences for adolescents and comparability between on- and off-line contexts. A review of relevant research revealed that when asked about the types of Table 1 Demographics. Characteristic
Study 1 (%)
Study 2 (%)
Age 14 15 16 17
20.2 69.7 9.1 1.1
69.4 30.6 0 0
Gender Female Male
50.6 49.4
63.8 36.2
Grade 9th 10th
56.2 43.8
100 0
Ethnicity Caucasian/White African-American/Black Asian Other
73 5.6 13.5 5.6
83.3 2.8 8.3 5.6
When use SNS Before school During school Early afternoon Evening Bedtime
21.3 6.7 37.1 79.8 36
13.9 22.2 25 83.3 50
Skill on SNS Beginner Experienced Expert
21.3 50.6 28.1
19.4 61.1 19.4
Daily hours on SNS 0 1 2 3 4+
11.2 47.2 24.7 9 7.8
13.9 52.8 16.7 8.3 5.6
Use Internet at least once a day for Facebook MySpace Twitter YouTube Formspring Email AIM GChat Class assignments Chat rooms
79.8 0 2.2 52.8 4.5 73.1 4.5 5.6 52.8 1.1
80.6 0 21.2 47.1 0 70.6 6.7 3.3 67.6 3.2
Note. SNS = Social Networking Sites.
bullying victims experience, respondents’ answers most frequently involve being teased, the subject of rumors, threatened, pictures displayed by others without consent, physically hurt, intentionally excluded, or ignored (Aricak et al., 2008; Patchin & Hinduja, 2006; Seals & Young, 2003). Of these categories of bullying, the scenarios constructed needed to be presentable in comparative formats across mediums. Behavior that involved threat of OA and RA (specifically, teasing/embarrassing) was selected to allow for direct comparisons on- and off-line. All scenarios were taken from the popular media to ensure high production quality and relevancy of the content to adolescents. In the RA scenario, the off-line bullying example consisted of a video clip where a group of school-aged adolescents distribute an embarrassing picture of the victim during the school day. At lunch, they show the female victim’s photograph to her in front of her peers. Her peers laugh at her, and she becomes visibly upset and runs out of the cafeteria. The electronic bullying example consisted of a snapshot of a Facebook page where the bully posted an embarrassing picture of the female victim on the victim’s wall and many people are commenting about it and making hurtful and insulting statements. In the threat of OA scenario, the off-line bullying example showed the female victim mildly flirting with the bully’s boyfriend. The victim then found the word ‘‘slut’’ written on her school locker. The bully confronted the victim and threatened to hit her after school. The electronic bullying example showed snapshots of two profiles and the wall-to-wall dialog between the two profiles. On the female victim’s profile, some flirtatious pictures of the victim and the bully’s boyfriend were included. The wall posts between the bully and victim showed the bully calling the victim a slut and threatening to beat her up the next day. 3.1.3. Procedures During the study, adolescents were seated in front of a computer with headphones. They were directed to a webpage that briefly described the study and asked demographic questions. Each adolescent viewed the two bullying conditions (threat of OA and RA) in both off-line and online forms. Presentation of the four bullying scenarios was counterbalanced. After each scenario was presented, the adolescents were first asked to identify who was the victim. This served as a manipulation check, and ensured that the adolescent was paying attention to the stimuli before answering the study questions. The primary study questions were designed to examine how adolescents problem solve in a bullying situation. Adolescents were asked to rate how they would feel in such a situation if they were the victim on a number of emotions and how it might disrupt their typical activities. Adolescents then provided information on how they might respond if they were the victim, and how important different outcomes or goals would be. The answer choices provided were selected from several prior studies based on the responses that were included and endorsed most often (Craig et al., 2007; Dehue et al., 2008; Patchin & Hinduja, 2006). Adolescents were also given several open-ended prompts (e.g., after being asked to rate the general impact of traditional vs. Facebook bullying, adolescents were asked ‘‘Why?’’ and given space to respond). These data were analyzed qualitatively. 3.2. Results and discussion A total of 89 students were used in the analysis. A repeated measures multivariate analysis of variance (MANOVA) was used to analyze each set of dependent variables (emotions and disruption in daily activity; responses to the bullying situation; desired outcomes or goals when responding to the situation). The within-subjects factors used were type of bullying (threat of overt
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aggression or relational aggression) and medium (electronic or offline). Gender of the participant was used as a between-subjects variable, and no systematic differences in responses by male vs. female adolescents were found. Statistical test assumptions were not violated and no effect due to counterbalancing was found. Ratings of negative emotions and disruption in daily activities indicated that video clips and Facebook snapshots impacted adolescents in the expected manner, consistent with prior literature (see Table 2). Students were asked to rate how they would feel if they were the victim in the bullying situation on a scale from 1 (much less than usual) to 5 (much more than usual), with 3 indicating ‘‘same as usual’’ to allow for directionality, and adolescents to serve as their own controls. No significant effects from the MANOVA were noted, suggesting that neither the medium (traditional vs. Facebook) nor the type of bullying (OA vs. RA) had a consistent effect on which emotions participants noted they would experience. As can be seen in Table 2, participants reported that they would experience negative emotions in response to bullying regardless of medium or type.
Table 3 Repeated measures ANOVAs comparing responses to electronic and traditional bullying, for OA and RA scenarios. Item
Tell friend Tell adult Do nothing Ask bully to stop Bully the bully Bully others Avoid Facebook Avoid school Joke about it Plot revenge Report to authorities *
3.2.1. Analysis of the ways to respond to Facebook and traditional bullying Students were then asked how they would respond if they were the victim in the bullying situation on a scale from 1 (would not do it) to 5 (would do it). MANOVA results suggested two interaction effects. A significant interaction between medium (traditional vs. Facebook) and response (Wilks’ Lambda = .74, F(10, 68) = 2.45, p < .02, partial eta squared = .265) suggests that students are more likely to choose certain responses when bullying happens in a traditional setting as opposed to electronic. A significant interaction between bullying type (OA vs. RA) and response suggests that students are more likely to choose certain responses when dealing with OA vs. dealing with RA (Wilks’ Lambda = .77, F(10,68) = 2.05, p < .05, partial eta squared = .23). Follow up ANOVA results (see Table 3) indicate that students are more likely to tell an adult when an off-line bullying situation occurred, as compared to an incident of electronic bullying (electronic OA condition M = 2.66, SD = 1.33 vs. off-line OA condition: M = 2.84, SD = 1.34; electronic RA condition: M = 2.81, SD = 1.41 vs. off-line RA condition: M = 3.11, SD = 1.39). Given adults’ comparatively limited experience with technology and online communication, it is not surprising that Table 2 Means and standard deviations of emotions and disruption in typical activities for Study 1. Item
OA
RA
Online
Sad Angry Embarrassed Afraid Bad about myself Trusting of othersa Alone or lonely Want to go to schoola Want to go onlinea
Off-line
Online
Off-line
M
SD
M
SD
M
SD
M
SD
3.59** 4.38** 3.72** 3.84** 3.43**
0.96 0.86 1.12 1.13 1.06
3.36** 4.25** 3.71** 3.79** 3.35*
0.93 0.84 1.01 1.17 1.09
3.90** 4.19** 4.49** 3.45** 3.62**
1.01 0.85 0.77 1.07 1.17
4.03** 4.35** 4.58** 3.63** 3.73**
0.99 0.84 0.80 1.13 1.22
2.31**
1.04
2.30**
0.90
2.08**
1.14
2.08**
1.25
3.19
1.12
3.00
0.95
3.46**
1.13
3.52**
1.33
1.93**
0.88
2.01**
0.86
1.90**
0.87
1.75**
0.98
2.24**
0.97
2.51**
0.88
1.90**
1.06
2.02**
1.07
Note. Scale ranges from ‘‘1: Much less than usual’’ to ‘‘5: Much more than usual’’ to allow for directionality, with ‘‘3: Same as usual’’. a Reverse coded. * p < .05. ** p < .01.
Main effect of electronic vs. traditional
Main effect of OA vs. RA
Interaction
F(1,88)
Partial eta2
F(1,88)
Partial eta2
F(1,88)
Partial eta2
0.02 11.00* 3.29 1.14
.000 .111 .036 .013
1.29 3.17 2.53 0.10
.014 .035 .028 .001
3.18 0.95 2.86 0.72
.035 .011 .031 .008
0.33 0.02 6.56*
.004 .000 .071
3.24 0.31 10.76*
.036 .004 .111
0.26 0.01 7.67*
.003 .000 .082
0.75 0.94 4.69* 0.19
.009 .011 .052 .001
1.42 0.20 0.38 3.65
.016 .002 .541 .040
8.36* 0.11 0.00 1.40
.088 .001 .000 .016
p < .05.
students rated themselves more likely to seek adult assistance when bullying occurs in an off-line setting. The significant ANOVA interaction effect for this dependent variable indicates that adolescents were most likely to seek adult assistance when embarrassment bullying occurred in a traditional setting. Additionally, follow up ANOVA results indicate that adolescents reported an even greater likelihood of avoiding Facebook after experiencing relational aggression online (electronic OA condition M = 2.78, SD = 1.27 vs. off-line OA condition: M = 2.32, SD = 1.09; electronic RA condition: M = 2.95, SD = 1.24 vs. off-line RA condition: M = 2.91, SD = 1.34). This may be related to the large audience that can see bullying online, which is particularly distressing when embarrassment is the goal of the relationally aggressive bullying behavior. Unfortunately, given the high usage of electronic and social media among youth the strategy of avoidance is likely to be isolating, ineffective, and not maintained. 3.2.2. Analysis of the desired outcomes in response to Facebook and traditional bullying Students were asked how important different outcomes would be if they were the victim in the bullying situation on a scale from 1 (not important) to 5 (extremely important). An omnibus MANOVA analysis indicates a three-way interaction effect for medium (traditional vs. Facebook), bullying type (OA vs. RA), and the goals that students endorsed as important (Wilks’ Lambda = .88, Table 4 Repeated measures ANOVAs comparing desired outcomes when responding to electronic and traditional bullying, for OA and RA scenarios. Item
Bullying to stop Get along with bully Keep friends Feel better Maintain reputation * **
p < .05. p < .001.
Main effect of electronic vs. traditional
Main effect of OA vs. RA
Interaction
F(1,88)
Partial eta2
F(1,88)
F(1,88)
0.01
.000
1.05
0.36
.004
2.99
3.18 0.19 1.00
.035 .002 .011
*
6.87 13.27** 0.46
Partial eta2 .012
0.98
.034
1.50
.072 .131 .005
Partial eta2 .011 .017
*
10.53 8.11* 0.73
.107 .084 .008
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F(4, 82) = 2.72, p < .04, partial eta squared = .12). Follow up ANOVA analyses (see Table 4) revealed two dependent variables (‘‘keep friends’’ and ‘‘feel better’’) that students indicated would be most important to them when the scenario involved RA that occurred in an off-line format (Keep friends: electronic OA M = 4.18, SD = .972 vs. off-line OA: M = 3.91, SD = 1.11; electronic RA: M = 4.19, SD = 1.09 vs. off-line RA: M = 4.27, SD = 1.00; Feel better: electronic OA M = 4.28, SD = .941 vs. off-line OA: M = 4.11, SD = .994; electronic RA: M = 4.44, SD = .839 vs. off-line RA: M = 4.56, SD = .783). Overall, students indicated that getting the bullying behavior to stop and feeling better were the most important outcomes in a bullying situation. 4. Study 2 4.1. Introduction and method OA and RA scenarios in Study 1 involved female adolescents only, and research to date has found mixed results regarding the role of gender in both traditional and electronic bullying. Therefore, Study 2 seeks to examine the impact of gender of characters in a bullying scenario on adolescents’ perceptions of bullying. Some prior literature suggests that, consistent with gender role expectations, girls were more likely to be victims of electronic bullying (Dehue et al., 2008; Lenhart; 2007; Li, 2007; Smith et al., 2008), and boys were more likely to be bullies online (Dehue et al., 2008; Li, 2006). In other studies, however, no gender effects are found, and males and females were equally likely to be online bullies and victims (Beran & Li, 2005; Patchin & Hinduja, 2006; Slonje & Smith, 2008; Ybarra & Mitchell, 2004). In the studies where no gender effects are found, the lack of a significant difference between genders in electronic bullying suggests that females participate in electronic bullying more than they do in traditional bullying (Smith et al., 2008). This finding stands in comparison to traditional, off-line bullying, which studies suggest occurs more often among males (e.g., Smith et al., 2008). Given the potentially different experiences that males and females have with traditional bullying and electronic bullying, Study 2 replicates the on and off line OA scenario for Study 1, and adds an additional overt aggression scenario with male characters as bully and victim. Thus, there was a direct comparison for the OA of threat by gender. 4.1.1. Participants The students for the second study were selected from the same large public high school near a major Northeast city. Students were recruited through announcements in their study hall classrooms and via email. A total of 47 students, of approximately 450 eligible students, had parental consent, provided assent, and completed the study. This was an independent sample, with no overlap in s from Study 1. Students’ responses were first examined to ensure they were attending to the stimuli and identified the correct person as the victim of bullying. After this initial analysis, 11 adolescents’ data were dropped from subsequent analyses, leaving a sample of 36. Adolescents were asked to provide demographic information, summarized in Table 1. 4.1.2. Development of stimuli and procedures The same OA scenario with female characters was used. In addition, a second OA scenario with male characters was taken from the popular media and edited to be similar in length to the clip with female characters. The video clip of the male traditional bullying example showed four high school-age adolescents accosting a younger student in the hall and saying disrespectful things about his physical appearance. Then, one of the largest students threatens to beat up the victim student after school while the others look
on and laugh. The electronic bullying example shows the same comments being made via Facebook ‘‘comments’’ about the victim students’ ‘‘Facebook wall’’. The threat was also written on the ‘‘Facebook wall’’. The actually study questions were the same as Study 1. Procedures used were identical to Study 1. 4.2. Results and discussion A total of 36 students were used in the analysis. A repeated measures multivariate analysis of variance (MANOVA) was used to analyze each set of dependent variables (emotions and disruption in daily activity; responses; desired outcomes or goals). The within-subjects factors used were gender of character in bullying scenario (female or male) and medium (electronic or off-line). Gender of the participant was used as a between-subjects variable, in order to assess any gender differences in participant responses. Statistical test assumptions were not violated and no effect due to counterbalancing was found. To ensure that the video clips and Facebook snapshots used in the study had an impact on the adolescents in the intended direction, ratings of negative emotions and disruption in typical activities were examined. Students reported negative emotions and disruption in typical activities equal to or more than usual after watching a bullying scenario. All means were in hypothesized direction. Additionally, almost all of the students’ average ratings were significantly different from how they usually feel if they were the victim in the bullying situation (‘‘same as usual’’ coded as ‘‘3’’) based on a series of one sample t-tests. This suggests the stimuli impacted the s in the intended manner (see Table 6). 4.2.1. Analysis of the impact of Facebook and traditional bullying An omnibus MANOVA analysis indicated a significant interaction between gender of the characters in the scenario (male or female) and emotion (Wilks’ Lambda = .46, F(8,26) = 3.86, p < .01, partial eta squared = .54), indicating that adolescents frequently viewed scenarios with male characters as inducing more negative emotions than scenarios with female characters (for means and standard deviations, see Table 5). Given that past research indicates that OA among males is more likely than among females (Pepler, Jiang, Craig, & Connolly, 2008), it is interesting to note that both male and female students viewed the male OA bullying
Table 5 Means and standard deviations of emotions and disruption in typical activities for Study 2. Item
OA – Male characters Online
Sad Angry Embarrassed Afraid Bad about myself Trusting of othersa Alone or lonely Want to go to schoola Want to go onlinea
OA – Female characters
Off-line
Online
Off-line
M
SD
M
SD
M
SD
M
SD
4.36** 4.47** 4.50** 4.50** 4.33**
0.72 0.70 0.78 0.66 0.72
4.36** 4.58** 4.42** 4.58** 4.22**
0.80 0.60 0.77 0.65 0.80
3.81** 4.39** 3.89** 3.89** 3.81**
0.82 0.65 0.92 1.09 0.92
3.72** 4.36** 4.03** 3.92** 3.78**
0.85 0.93 0.97 1.03 0.87
3.56*
1.28
3.75**
1.27
3.33
1.12
3.64**
1.02
**
4.03
1.03
4.17
**
0.94
3.42
4.28**
0.88
4.36**
0.90
4.33**
0.93
4.06**
1.07
*
*
1.05
3.34
0.91
3.78**
1.05
4.00**
0.89
3.94**
1.09
3.78**
0.87
Note. Scale ranges from ‘‘1: Much less than usual’’ to ‘‘5: Much more than usual’’ to allow for directionality, with ‘‘3: Same as usual’’. a Reverse coded. * p < .05. ** p < .01.
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S. Horner et al. / Computers in Human Behavior 49 (2015) 288–295 Table 6 Repeated measures ANOVAs comparing responses to electronic and traditional bullying, for scenarios with male and female characters. Item
Tell friend Tell adult Do nothing Ask bully to stop Bully the bully Bully others Avoid Facebook Avoid school Joke about it Plot revenge Report to authorities *
Main effect of electronic vs. traditional
Main effect of male characters vs. female characters
Interaction
F(1,35)
Partial eta2
F(1,35)
Partial eta2
F(1,35)
Partial eta2
1.76 5.85* 0.01 3.05
.048 .143 .000 .082
0.89 5.09* 0.16 1.09
.025 .127 .005 .031
1.86 0.00 0.01 0.05
.050 .000 .000 .002
1.00 0.36 2.46
.026 .010 .066
5.00* 0.66 4.14*
.125 .019 .106
0.00 0.55 1.09
.000 .016 .030
3.15 0.64 1.29 0.52
.083 .018 .036 .015
4.53* 8.66* 4.53* 5.08*
.115 .198 .115 .127
1.55 4.58* 0.15 0.02
.042 .116 .004 .001
p < .05.
scenarios as more emotionally upsetting. It is unclear if this higher level of emotional distress is due to an expectation of greater physical harm with male vs. female OA or some other factors. 4.2.2. Analysis of the ways to respond to Facebook and traditional bullying Students were then asked how they would respond if they were the victim in the bullying situation. MANOVA results suggest a three-way interaction between gender of the characters in the scenario (male or female), response, and the adolescent’s gender (Wilks’ Lambda = .45, F(10,23) = 2.85, p < .02, partial eta squared = .55). Follow up ANOVA analyses did not support differences related to participant’s gender. However, additional ANOVA analyses (see Table 6) indicated that participants would be more likely to use the following strategies when a bullying situation involved male characters, regardless of the medium in which the bullying occurred: avoid Facebook, avoid school, report to authorities. In contrast, students reported that they would be more likely to use the following strategies when a bullying situation involved female characters, regardless of the medium in which the bullying occurred: bully the bully, plot revenge. Interestingly, for bullying involving male characters the general preference is for the victim to avoid peers, in contrast, for bullying involving female characters the more likely strategy employed by the victim is to directly retaliate against the bully. One possible explanation for this finding may be due to the differing nature of female vs. male aggression. In particular, females more often employ RA and among high school students this has less potential social cost than OA. Thus, adolescents’ willingness to employ retaliatory strategies when reacting to female bullies may reflect a belief that relationally aggressive behavior is a potentially cost effective option. Further research is needed to explore this greater likelihood for students to utilize retaliation when responding to female bullies. Some notable differences between electronic and traditional bullying did emerge through the open-ended questions. Several students wrote that the ambiguity of threats delivered online were a particular challenge. For example, one adolescent noted that, ‘‘on Facebook, it is much more difficult to read people’s feelings or reactions. If someone was to threaten another person online, it would not be easy to determine the seriousness of the situation like it would be if it happened in person’’. Another stated that threats online are ‘‘worse because you cannot see the person’s reaction and you do not know the tone of how they are saying it’’. These
Table 7 Repeated measures ANOVAs comparing desired outcomes when responding to electronic and traditional bullying, for scenarios with male and female characters. Item
Bullying to stop Get along with bully Keep friends Feel better Maintain reputation *
Main effect of electronic vs. traditional
Main effect of male characters vs. female characters
Interaction
F(1,35)
Partial eta2
F(1,35)
Partial eta2
F(1,35)
Partial eta2
0.47
.013
8.45*
.194
0.05
.001
0.12
.003
2.76
.073
0.00
.000
0.02 0.53 0.00
.000 .016 .000
0.02 0.06 4.53*
.000 .002 .118
0.04 2.06 0.14
.001 .059 .004
p < .05.
comments suggest that although students report both on and offline bullying are similar in the general level of distress, they appreciate of the structural differences in the medium of communication. 4.2.3. Analysis of the desired outcomes in response to Facebook and traditional bullying Students were asked how important different outcomes would be if they were the victim in the bullying situation. MANOVA results reveal an interaction between gender of the characters in the scenario (male or female) and goals the adolescent reports as being important (Wilks’ Lambda = .72, F(4,29) = 2.85, p < .05, partial eta squared = .28), suggesting adolescents view different outcomes of a bullying situation as important when the situation involves males bullying as opposed to females bullying. Follow up ANOVA analyses (see Table 7) indicate that maintaining one’s reputation is most important to adolescents when the scenario involved female characters, as opposed to male characters (online male characters M = 3.20, SD = 1.23 vs. off-line male characters M = 3.17, SD = 1.29; online female characters M = 3.51, SD = 1.10 vs. off-line female characters M = 3.54, SD = 1.04). This finding is consistent with the high importance that adolescent females place on their social reputation. In addition, students indicated that the goal of having the bullying stop would be more important when the bullying situation involved male characters, as opposed to female characters (Bullying to stop: online male characters M = 4.67, SD = .862 vs. off-line male characters M = 4.64, SD = .899; online female characters M = 4.39, SD = .964 vs. off-line female characters M = 4.33, SD = 1.15). It may be that male bullies are perceived as more threatening than female bullies. Further research is needed to understand why this might be the case. 5. General discussion The current studies examined high-school adolescents’ perceptions of electronic and traditional bullying through having students observe hypothetical scenarios, imagine themselves as the victim, and then describe the impact, responses, and goals in resolving the bullying scenarios. As predicted, across all scenarios, students indicated a significant negative impact of bullying situations highlighting the emotions of sadness, anger, embarrassment, fear, and losing trust in others. However, there was a difference found for the strategies most endorsed in response to bullying as related to the gender of the characters involved. When the characters were male, participants of both genders were more likely to endorse strategies of avoidance of the bully. In contrast, when the characters involved (both bully and victim) were female, participants of
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both genders were more likely to endorse strategies of retaliation requiring increased contact between the protagonists. High-school students also indicated the strategy of behavioral avoidance of the context (avoiding school or online activities) where they as the victim might encounter those who had witnessed the bullying. This suggests that the witness or bystander to bullying becomes a negative stimulus in addition to the actual bully. Both on- and off-line, the negative emotional reaction and disruption in typical daily activities demonstrates the high personal cost of peer victimization on adolescents across widely divergent bullying scenarios (e.g., Bonanno & Hymel, 2013; Sticca & Perren, 2013). Overall, across a range of bullying situations (RA or OA, male or female protagonists) there were many similarities in the nature of student reactions to electronic and traditional bullying. As suggested by Bauman and Newman (2012), electronic bullying appears to be a sub-type of the broader category of ‘‘bullying behaviors’’, with concomitant negative outcomes, not a separate and unique phenomenon. This is consistent with preliminary research examining differences between equivalent bullying behaviors on- and off-line among adolescents and young adults (Bauman & Newman, 2013; Sticca & Perren, 2013). It is likely that adolescents experience online and social media activities as an integrated part of their everyday lives. The negative impact of bullying seemed to vary more in response to the type of bullying, overt or relational aggression, or by the gender of the protagonists than by whether the bullying occurred on- vs. off-line. Consistent with the framework of egocentrism and heightened social sensitivity (Buhrmester & Furman, 1987), many of the adolescents’ responses to the open-ended questions in Study 1 indicate the importance of their peer group, and spectators’ potential judgments or opinions. For example, students wrote in response to the relational aggression scenario that it would be particularly hurtful, ‘‘Because all of your friends can see it’’, ‘‘In this situation, it was completely public for all of their friends to see, and they have a whole lot of friends. Also, it can’t be taken back or denied’’, ‘‘Everyone can see everything on Facebook’’, and ‘‘Facebook bullying only hurts your reputation, and maybe your feelings’’. These responses highlight that the victims’ awareness of an audience has a powerful negative impact when being bullied. Given the distinct nature of in-person vs. electronic audiences (e.g., number of witnesses, temporal stability, abstraction) the nature of the embarrassment and distress resulting from bullying in the two mediums needs further exploration. The public nature of the bullying matters and bystanders are not viewed as benign observers but as peers with the potential to judge the victim. Although adolescents in Study 2 emphasized fear in the OA scenarios, adolescents in both studies noted that embarrassment was a powerful emotion connected to all bullying situations. The heightened concern about peers’ viewpoints is highly relevant to adolescents’ experience of being bullied both on- and off-line, and thus needs to be taken into consideration when designing prevention and intervention programs. For example, strengthening adolescents’ positive friendships and building new relationships may help adolescents to diminish the disruptive power of the imaginary audience. One intervention program, described by Slonje, Smith, and Frisén (2013) involves adolescents forming small workgroups at school to deal with specific issues of cyberbullying. This may be a particularly effective intervention because it not only places technology-savvy adolescents at the forefront of problem solving, but also allows adolescents in these groups to form positive peer relationships, thereby improving the school climate. As the current study was an early step in understanding adolescents’ perceptions of electronic and traditional bullying using an experimental design, there are important limitations to be addressed through future research. First, the OA scenario was
reported by adolescents to be both threatening (characteristic of OA) and embarrassing (characteristic of RA; in both Study 1 and Study 2). Given how critical embarrassment is to adolescents, it is unclear if all bullying situations involving OA would be embarrassing, or if this is specific to the scenario chosen, where there was an audience present. Early experimental research on electronic bullying has focused on anger and sadness as responses to bullying, leaving out embarrassment entirely (Pieschl et al., 2013). Thus, further research on the frequency and strength of embarrassment in response to electronic bullying is important. Second, given the rapidly changing format of online communication, some emerging popular forms of communication were not assessed (e.g., Snap Chat, Twitter, Instagram). Third, due to the small sample size in Study 2, it was not possible statistically to compare victim gender (in the bullying scenarios presented) with adolescents’ gender. Prior experimental and self-report studies yield mixed findings with regard to the role of gender in electronic bullying, particularly when directly compared with traditional bullying (e.g., Pieschl et al., 2013; Slonje et al., 2013). Therefore, future research should include more varied bullying scenarios (e.g., a wider range of relationally aggressive behaviors), with the gender of bullies and victims manipulated. This will allow for further exploration of gender differences in responses to a variety of electronic and traditional bullying situations. Overall, given the significant impact, negative emotional reaction, and disruption in typical daily activities of both electronic and traditional bullying (e.g., Bauman & Newman, 2013; Bonanno & Hymel, 2013), adults in adolescents’ lives must recognize the importance of addressing bullying when it occurs both on- and offline. The high acceptance of avoidance strategies in response to bullying is particularly worrisome as it may lead to isolation and reduces the opportunity for positive peer experiences. Given the high degree to which adolescents value the viewpoint of peers, plus their heightened sensitivity to being publically embarrassed, victims may mistakenly avoid those students who could actually be a resource. Initial literature suggests that boys may be more likely to avoid seeking social support when confronted with electronic bullying, and may particularly benefit from interventions designed to combat this tendency (Pieschl et al., 2013). Bystanders and friends are likely to be a critical protective factor if they are able to mitigate the victim’s sense of embarrassment. Future research needs to examine how best to empower adolescents to address the developmental challenges associated with social egocentrism.
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The impact and response to electronic bullying and traditional bullying among adolescents Stacy Horner a, Yvonne Asher b, Gary D. Fireman b,⇑ a b
Metrowest Neuropsychology, Westborough, MA, United States Department of Psychology, Suffolk University, United States
a r t i c l e
i n f o
Article history:
Keywords: Peer victimization Electronic bullying Adolescence
a b s t r a c t With adolescents’ frequent use of social media, electronic bullying has emerged as a powerful platform for peer victimization. The present two studies explore how adolescents perceive electronic vs. traditional bullying in emotional impact and strategic responses. In Study 1, 97 adolescents (mean age = 15) viewed hypothetical peer victimization scenarios, in parallel electronic and traditional forms, with female characters experiencing indirect relational aggression and direct verbal aggression. In Study 2, 47 adolescents (mean age = 14) viewed the direct verbal aggression scenario from Study 1, and a new scenario, involving male characters in the context of direct verbal aggression. Participants were asked to imagine themselves as the victim in all scenarios and then rate their emotional reactions, strategic responses, and goals for the outcome. Adolescents reported significant negative emotions and disruptions in typical daily activities as the victim across divergent bullying scenarios. In both studies few differences emerged when comparing electronic to traditional bullying, suggesting that online and off-line bullying are subtypes of peer victimization. There were expected differences in strategic responses that fit the medium of the bullying. Results also suggested that embarrassment is a common and highly relevant negative experience in both indirect relational and direct verbal aggression among adolescents. Ó 2015 Published by Elsevier Ltd.
1. Introduction Concern about school based bullying has recently grown to include peer aggression that occurs through social media. With the dramatic increase in adolescents’ use of social media and the time spent in unsupervised interaction on social media, there is a concurrent rise in opportunity for bullying within this medium. Prior to the rise of social media, bullying was typically conceptualized as the result of an exchange between at least two people, a bully and a victim, in direct face-to-face contact with each other. Given the scope of bullying and the potential damage to healthy development, the Center for Disease Control and Prevention and the Department of Education have recognized it as a significant public health concern. The CDC has provided a uniform definition to support effective scholarship, prevention and intervention: Any unwanted aggressive behavior(s) by another youth or group of youths who are not siblings or current dating partners
⇑ Corresponding author at: Department of Psychology, Suffolk University, Boston, MA 02114, United States. E-mail address: gfi[email protected] (G.D. Fireman). http://dx.doi.org/10.1016/j.chb.2015.03.007 0747-5632/Ó 2015 Published by Elsevier Ltd.
that involves an observed or perceived power imbalance and is repeated multiple times or is highly likely to be repeated. Bullying may inflict harm or distress on the targeted youth including physical, psychological, social, or educational harm (Gladden, Vivolo-Kantor, Hamburger, & Lumpkin, 2014, p. 7). Bullying that occurs through social media popularly referred to as ‘‘cyberbullying’’ is labeled ‘‘electronic bullying’’ by the CDC. Social media is an often-used form of interaction among adolescents with 95% of 12–17 year olds reporting utilization of the Internet (Lenhart et al., 2011). It should be noted that in electronic bullying the unwanted aggressive behavior may be perceived by the victim as repeated not due to repeated acts of the bully but rather, due to the enduring nature of electronic content with repeated viewings and potential for being shared widely. Given the distinct qualities of electronic bullying, questions arise regarding the nature and intensity of emotional and strategic responses of youth to electronic vs. traditional bullying. Being a victim of traditional bullying is connected to a number of negative academic, social, and psychological consequences (e.g., Nansel et al., 2001; Rigby & Slee, 1991). Similar negative consequences have been reported through survey research for victims
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of electronic bullying, including school avoidance, truancy, eating disorders, depression, poor self-esteem, and suicidal ideation or suicide (e.g., Schneider, O’Donnell, Stueve, & Coulter, 2012). However, despite the tragic examples of electronic bullying reflected in the media, little experimental research distinguishing electronic bullying from traditional bullying has been completed (for exceptions, see Pieschl, Porsch, Kahl, & Klockenbusch, 2013; Sticca & Perren, 2013). The present research is one of a few initial efforts to move beyond correlational and retrospective designs by providing adolescents with specific hypothetical scenarios in order to examine how adolescents conceptualize and strategize about bullying and electronic bullying. The negative behaviors involved in bullying are often identified as direct, including overtly aggressive behaviors such as physical acts (e.g., pushing, punching) and verbal acts (e.g., insults, teasing), or indirect, which includes relationally aggressive acts designed to damage social relationships (e.g., spreading rumors, social exclusion). Similar to traditional bullying, most electronic bullying requires an intentional act committed by an individual or group in order to cause harm or distress to another individual or group but done through electronic communication technologies (Beran & Li, 2005; Mason, 2008). In one recent study, respondents were asked about different types of electronic bullying they were exposed to (Aricak et al., 2008) with 19% reporting threats while 81% reported some form of embarrassment (e.g., teasing, insults, rumors, or pictures displayed by others without consent). Although electronic bullying also requires a power differential between the bully and the victim (Mason, 2008), across online and off-line contexts the source of a bully’s strength and the reasons why a victim feels defenseless may vary considerably. As opposed to traditional bullying in which bullies often rely on a combination of attractiveness, local popularity, and physical strength as a source of power, it has been hypothesized that in electronic bullying the power is based more exclusively on a bully’s social connectedness and prestige all of which are visible on social networking site profiles (Patchin & Hinduja, 2006). For adolescents, who are especially concerned about what others think of them and are more likely to believe others are always watching (Elkind, 1967), electronic bullying that interrupts relationships, can be seen by many, and remains visible over time may be particularly upsetting. In the present research, the social media of Facebook was approximated and the numbers of ‘‘liked’’, tagged photos, and ‘‘friends’’ were all considered with the bully appearing more popular than the victim. As with traditional bullying, a number of negative consequences have been associated with electronic bullying. Self-report data indicate that adolescents who are victims of electronic bulling experience a number of emotional consequences (e.g., feelings of sadness, depression, anxiety, fear), as well as behavioral difficulties (e.g., missing school, difficulty concentrating, losing trust in peers, and falling grades; Beran & Li, 2005; Dehue, Bolman, & Völlink, 2008; Raskauskas & Stoltz, 2007) that are similar to traditional bullying (Bauman & Newman, 2013). Utilizing a retrospective self-report methodology with college students, Bauman and Newman (2013) found that perceived distress at a bullying situation was not consistently related to the form of bullying (i.e., electronic or traditional), but rather related to the factors involved in the specific situation. Similarly, Sticca and Perren (2013) note that ‘‘cyberbullying is not a priori perceived as worse than traditional bullying’’ (p. 739), but that certain factors (e.g., publicity of the bullying) determine adolescents’ perceived level of distress. Therefore, the present two studies examine adolescents’ emotional and strategic responses to bullying in distinct online and off-line scenarios. In a large self-report study, 1852 adolescents between the ages of 4 and 19 who had been bullied participated in an online survey about responses to traditional bullying (Craig, Pepler, & Blais,
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2007). Youth were presented with 12 possible strategies to cope with peer victimization (e.g., telling parents, telling other students, standing up to the bully, distraction, ignoring bullying), and asked to endorse which strategies they had utilized. The most frequent response, endorsed by approximately 50% of the respondents, was that they had tried to ignore the bullying. Smith et al. (2008) utilized large-scale surveys and focus groups to assess 11–16 year-olds’ beliefs regarding the best ways to stop electronic bullying. When provided with a list of possible ways to cope with electronic bullying, the most commonly endorsed strategies were to block messages/identities (75%), tell someone (63%), change email address/phone number (57%), and ignoring the behavior (41%). In traditional bullying prevention programs, telling an adult is often a recommended strategy. However, there is evidence to suggest that traditional victims are more likely to tell others than victims of electronic bullying (Smith et al., 2008). In research examining who victims tell about electronic bullying, the most frequent responses are to tell ‘‘no one’’ or ‘‘friends’’, with parents and teachers reported far less often (Aricak et al., 2008; Dehue et al., 2008; National Children’s Home, 2005; Slonje & Smith, 2008). It is possible that adolescents are more willing to tell friends (as opposed to parents or teachers) about both electronic and traditional bullying, as friends are an important source of social and emotional support during this developmental period. In addition, a substantial number of adolescents do not think school staff would or could do anything to stop electronic bullying (47%). These findings highlight the need to better understand if adolescents would respond differently to comparable bullying situations across off-line and online contexts in order to provide parents and professionals with guidance on how best to help those being bullied.
2. The present studies The present two studies build on the existing research by examining 9th and 10th grade adolescents’ perceptions of the impact and ways to respond to electronic bullying vs. traditional bullying. As mentioned above, the majority of research to date has used self-report survey methodologies, which have notable limitations (Raskauskas & Stoltz, 2007). The current research uses a design that allows adolescents to respond to specific hypothetical scenarios one focused on a situation involving threat of overt aggression (OA), and the other focused on a situation involving relational aggression (RA). These were chosen as prior research has suggested that threat of OA and RA (specifically, embarrassment) situations are the most commonly experienced types of bullying for adolescents (e.g., Aricak et al., 2008; Huang & Chou, 2010; Lenhart, 2007). Adolescents viewed the same scenarios in both traditional and online formats to make direct comparisons possible. Since December 2007, Facebook has become one of the most frequently used social networking sites (Smith, 2009b). Because of Facebook’s popularity among adolescents, the present research was designed to mimic this social networking site. The present research is divided into two distinct studies: the first study examined male and female adolescents’ responses to two scenarios, OA and RA, with female characters only. The second study replicates the OA scenario and adds the examination of male and female adolescents’ responses to an OA scenario with male characters (as opposed to female characters). Analyses focus on adolescents’ ratings of their emotional reactions and problem solving strategies in response to the bullying scenarios. We hypothesize that the bullying scenarios involving OA will elicit more negative emotion and distinct strategies in traditional vs. electronic platforms. In contrast, with RA, we hypothesize a more negative emotional impact online. We also predict that males will be more distressed by the OA bullying scenarios and females by the RA scenarios.
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3. Study 1 3.1. Methods 3.1.1. Participants Adolescents were selected from a large public high school near a major Northeast city. Adolescents were recruited through announcements in their study hall classrooms and via email. A total of 97 students, of approximately 450 eligible students, had parental consent, provided assent, and completed the study. Adolescents’ responses were first examined to ensure they were attending to the stimuli and identified the correct person as the victim of bullying. Eight students were not used in the following analysis (n = 89) because they failed to identify the correct victim. Adolescents were asked to provide demographic information, summarized in Table 1. 3.1.2. Development of stimuli The selection of specific scenarios was based on two key factors: representativeness of typical bullying experiences for adolescents and comparability between on- and off-line contexts. A review of relevant research revealed that when asked about the types of Table 1 Demographics. Characteristic
Study 1 (%)
Study 2 (%)
Age 14 15 16 17
20.2 69.7 9.1 1.1
69.4 30.6 0 0
Gender Female Male
50.6 49.4
63.8 36.2
Grade 9th 10th
56.2 43.8
100 0
Ethnicity Caucasian/White African-American/Black Asian Other
73 5.6 13.5 5.6
83.3 2.8 8.3 5.6
When use SNS Before school During school Early afternoon Evening Bedtime
21.3 6.7 37.1 79.8 36
13.9 22.2 25 83.3 50
Skill on SNS Beginner Experienced Expert
21.3 50.6 28.1
19.4 61.1 19.4
Daily hours on SNS 0 1 2 3 4+
11.2 47.2 24.7 9 7.8
13.9 52.8 16.7 8.3 5.6
Use Internet at least once a day for Facebook MySpace Twitter YouTube Formspring Email AIM GChat Class assignments Chat rooms
79.8 0 2.2 52.8 4.5 73.1 4.5 5.6 52.8 1.1
80.6 0 21.2 47.1 0 70.6 6.7 3.3 67.6 3.2
Note. SNS = Social Networking Sites.
bullying victims experience, respondents’ answers most frequently involve being teased, the subject of rumors, threatened, pictures displayed by others without consent, physically hurt, intentionally excluded, or ignored (Aricak et al., 2008; Patchin & Hinduja, 2006; Seals & Young, 2003). Of these categories of bullying, the scenarios constructed needed to be presentable in comparative formats across mediums. Behavior that involved threat of OA and RA (specifically, teasing/embarrassing) was selected to allow for direct comparisons on- and off-line. All scenarios were taken from the popular media to ensure high production quality and relevancy of the content to adolescents. In the RA scenario, the off-line bullying example consisted of a video clip where a group of school-aged adolescents distribute an embarrassing picture of the victim during the school day. At lunch, they show the female victim’s photograph to her in front of her peers. Her peers laugh at her, and she becomes visibly upset and runs out of the cafeteria. The electronic bullying example consisted of a snapshot of a Facebook page where the bully posted an embarrassing picture of the female victim on the victim’s wall and many people are commenting about it and making hurtful and insulting statements. In the threat of OA scenario, the off-line bullying example showed the female victim mildly flirting with the bully’s boyfriend. The victim then found the word ‘‘slut’’ written on her school locker. The bully confronted the victim and threatened to hit her after school. The electronic bullying example showed snapshots of two profiles and the wall-to-wall dialog between the two profiles. On the female victim’s profile, some flirtatious pictures of the victim and the bully’s boyfriend were included. The wall posts between the bully and victim showed the bully calling the victim a slut and threatening to beat her up the next day. 3.1.3. Procedures During the study, adolescents were seated in front of a computer with headphones. They were directed to a webpage that briefly described the study and asked demographic questions. Each adolescent viewed the two bullying conditions (threat of OA and RA) in both off-line and online forms. Presentation of the four bullying scenarios was counterbalanced. After each scenario was presented, the adolescents were first asked to identify who was the victim. This served as a manipulation check, and ensured that the adolescent was paying attention to the stimuli before answering the study questions. The primary study questions were designed to examine how adolescents problem solve in a bullying situation. Adolescents were asked to rate how they would feel in such a situation if they were the victim on a number of emotions and how it might disrupt their typical activities. Adolescents then provided information on how they might respond if they were the victim, and how important different outcomes or goals would be. The answer choices provided were selected from several prior studies based on the responses that were included and endorsed most often (Craig et al., 2007; Dehue et al., 2008; Patchin & Hinduja, 2006). Adolescents were also given several open-ended prompts (e.g., after being asked to rate the general impact of traditional vs. Facebook bullying, adolescents were asked ‘‘Why?’’ and given space to respond). These data were analyzed qualitatively. 3.2. Results and discussion A total of 89 students were used in the analysis. A repeated measures multivariate analysis of variance (MANOVA) was used to analyze each set of dependent variables (emotions and disruption in daily activity; responses to the bullying situation; desired outcomes or goals when responding to the situation). The within-subjects factors used were type of bullying (threat of overt
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aggression or relational aggression) and medium (electronic or offline). Gender of the participant was used as a between-subjects variable, and no systematic differences in responses by male vs. female adolescents were found. Statistical test assumptions were not violated and no effect due to counterbalancing was found. Ratings of negative emotions and disruption in daily activities indicated that video clips and Facebook snapshots impacted adolescents in the expected manner, consistent with prior literature (see Table 2). Students were asked to rate how they would feel if they were the victim in the bullying situation on a scale from 1 (much less than usual) to 5 (much more than usual), with 3 indicating ‘‘same as usual’’ to allow for directionality, and adolescents to serve as their own controls. No significant effects from the MANOVA were noted, suggesting that neither the medium (traditional vs. Facebook) nor the type of bullying (OA vs. RA) had a consistent effect on which emotions participants noted they would experience. As can be seen in Table 2, participants reported that they would experience negative emotions in response to bullying regardless of medium or type.
Table 3 Repeated measures ANOVAs comparing responses to electronic and traditional bullying, for OA and RA scenarios. Item
Tell friend Tell adult Do nothing Ask bully to stop Bully the bully Bully others Avoid Facebook Avoid school Joke about it Plot revenge Report to authorities *
3.2.1. Analysis of the ways to respond to Facebook and traditional bullying Students were then asked how they would respond if they were the victim in the bullying situation on a scale from 1 (would not do it) to 5 (would do it). MANOVA results suggested two interaction effects. A significant interaction between medium (traditional vs. Facebook) and response (Wilks’ Lambda = .74, F(10, 68) = 2.45, p < .02, partial eta squared = .265) suggests that students are more likely to choose certain responses when bullying happens in a traditional setting as opposed to electronic. A significant interaction between bullying type (OA vs. RA) and response suggests that students are more likely to choose certain responses when dealing with OA vs. dealing with RA (Wilks’ Lambda = .77, F(10,68) = 2.05, p < .05, partial eta squared = .23). Follow up ANOVA results (see Table 3) indicate that students are more likely to tell an adult when an off-line bullying situation occurred, as compared to an incident of electronic bullying (electronic OA condition M = 2.66, SD = 1.33 vs. off-line OA condition: M = 2.84, SD = 1.34; electronic RA condition: M = 2.81, SD = 1.41 vs. off-line RA condition: M = 3.11, SD = 1.39). Given adults’ comparatively limited experience with technology and online communication, it is not surprising that Table 2 Means and standard deviations of emotions and disruption in typical activities for Study 1. Item
OA
RA
Online
Sad Angry Embarrassed Afraid Bad about myself Trusting of othersa Alone or lonely Want to go to schoola Want to go onlinea
Off-line
Online
Off-line
M
SD
M
SD
M
SD
M
SD
3.59** 4.38** 3.72** 3.84** 3.43**
0.96 0.86 1.12 1.13 1.06
3.36** 4.25** 3.71** 3.79** 3.35*
0.93 0.84 1.01 1.17 1.09
3.90** 4.19** 4.49** 3.45** 3.62**
1.01 0.85 0.77 1.07 1.17
4.03** 4.35** 4.58** 3.63** 3.73**
0.99 0.84 0.80 1.13 1.22
2.31**
1.04
2.30**
0.90
2.08**
1.14
2.08**
1.25
3.19
1.12
3.00
0.95
3.46**
1.13
3.52**
1.33
1.93**
0.88
2.01**
0.86
1.90**
0.87
1.75**
0.98
2.24**
0.97
2.51**
0.88
1.90**
1.06
2.02**
1.07
Note. Scale ranges from ‘‘1: Much less than usual’’ to ‘‘5: Much more than usual’’ to allow for directionality, with ‘‘3: Same as usual’’. a Reverse coded. * p < .05. ** p < .01.
Main effect of electronic vs. traditional
Main effect of OA vs. RA
Interaction
F(1,88)
Partial eta2
F(1,88)
Partial eta2
F(1,88)
Partial eta2
0.02 11.00* 3.29 1.14
.000 .111 .036 .013
1.29 3.17 2.53 0.10
.014 .035 .028 .001
3.18 0.95 2.86 0.72
.035 .011 .031 .008
0.33 0.02 6.56*
.004 .000 .071
3.24 0.31 10.76*
.036 .004 .111
0.26 0.01 7.67*
.003 .000 .082
0.75 0.94 4.69* 0.19
.009 .011 .052 .001
1.42 0.20 0.38 3.65
.016 .002 .541 .040
8.36* 0.11 0.00 1.40
.088 .001 .000 .016
p < .05.
students rated themselves more likely to seek adult assistance when bullying occurs in an off-line setting. The significant ANOVA interaction effect for this dependent variable indicates that adolescents were most likely to seek adult assistance when embarrassment bullying occurred in a traditional setting. Additionally, follow up ANOVA results indicate that adolescents reported an even greater likelihood of avoiding Facebook after experiencing relational aggression online (electronic OA condition M = 2.78, SD = 1.27 vs. off-line OA condition: M = 2.32, SD = 1.09; electronic RA condition: M = 2.95, SD = 1.24 vs. off-line RA condition: M = 2.91, SD = 1.34). This may be related to the large audience that can see bullying online, which is particularly distressing when embarrassment is the goal of the relationally aggressive bullying behavior. Unfortunately, given the high usage of electronic and social media among youth the strategy of avoidance is likely to be isolating, ineffective, and not maintained. 3.2.2. Analysis of the desired outcomes in response to Facebook and traditional bullying Students were asked how important different outcomes would be if they were the victim in the bullying situation on a scale from 1 (not important) to 5 (extremely important). An omnibus MANOVA analysis indicates a three-way interaction effect for medium (traditional vs. Facebook), bullying type (OA vs. RA), and the goals that students endorsed as important (Wilks’ Lambda = .88, Table 4 Repeated measures ANOVAs comparing desired outcomes when responding to electronic and traditional bullying, for OA and RA scenarios. Item
Bullying to stop Get along with bully Keep friends Feel better Maintain reputation * **
p < .05. p < .001.
Main effect of electronic vs. traditional
Main effect of OA vs. RA
Interaction
F(1,88)
Partial eta2
F(1,88)
F(1,88)
0.01
.000
1.05
0.36
.004
2.99
3.18 0.19 1.00
.035 .002 .011
*
6.87 13.27** 0.46
Partial eta2 .012
0.98
.034
1.50
.072 .131 .005
Partial eta2 .011 .017
*
10.53 8.11* 0.73
.107 .084 .008
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S. Horner et al. / Computers in Human Behavior 49 (2015) 288–295
F(4, 82) = 2.72, p < .04, partial eta squared = .12). Follow up ANOVA analyses (see Table 4) revealed two dependent variables (‘‘keep friends’’ and ‘‘feel better’’) that students indicated would be most important to them when the scenario involved RA that occurred in an off-line format (Keep friends: electronic OA M = 4.18, SD = .972 vs. off-line OA: M = 3.91, SD = 1.11; electronic RA: M = 4.19, SD = 1.09 vs. off-line RA: M = 4.27, SD = 1.00; Feel better: electronic OA M = 4.28, SD = .941 vs. off-line OA: M = 4.11, SD = .994; electronic RA: M = 4.44, SD = .839 vs. off-line RA: M = 4.56, SD = .783). Overall, students indicated that getting the bullying behavior to stop and feeling better were the most important outcomes in a bullying situation. 4. Study 2 4.1. Introduction and method OA and RA scenarios in Study 1 involved female adolescents only, and research to date has found mixed results regarding the role of gender in both traditional and electronic bullying. Therefore, Study 2 seeks to examine the impact of gender of characters in a bullying scenario on adolescents’ perceptions of bullying. Some prior literature suggests that, consistent with gender role expectations, girls were more likely to be victims of electronic bullying (Dehue et al., 2008; Lenhart; 2007; Li, 2007; Smith et al., 2008), and boys were more likely to be bullies online (Dehue et al., 2008; Li, 2006). In other studies, however, no gender effects are found, and males and females were equally likely to be online bullies and victims (Beran & Li, 2005; Patchin & Hinduja, 2006; Slonje & Smith, 2008; Ybarra & Mitchell, 2004). In the studies where no gender effects are found, the lack of a significant difference between genders in electronic bullying suggests that females participate in electronic bullying more than they do in traditional bullying (Smith et al., 2008). This finding stands in comparison to traditional, off-line bullying, which studies suggest occurs more often among males (e.g., Smith et al., 2008). Given the potentially different experiences that males and females have with traditional bullying and electronic bullying, Study 2 replicates the on and off line OA scenario for Study 1, and adds an additional overt aggression scenario with male characters as bully and victim. Thus, there was a direct comparison for the OA of threat by gender. 4.1.1. Participants The students for the second study were selected from the same large public high school near a major Northeast city. Students were recruited through announcements in their study hall classrooms and via email. A total of 47 students, of approximately 450 eligible students, had parental consent, provided assent, and completed the study. This was an independent sample, with no overlap in s from Study 1. Students’ responses were first examined to ensure they were attending to the stimuli and identified the correct person as the victim of bullying. After this initial analysis, 11 adolescents’ data were dropped from subsequent analyses, leaving a sample of 36. Adolescents were asked to provide demographic information, summarized in Table 1. 4.1.2. Development of stimuli and procedures The same OA scenario with female characters was used. In addition, a second OA scenario with male characters was taken from the popular media and edited to be similar in length to the clip with female characters. The video clip of the male traditional bullying example showed four high school-age adolescents accosting a younger student in the hall and saying disrespectful things about his physical appearance. Then, one of the largest students threatens to beat up the victim student after school while the others look
on and laugh. The electronic bullying example shows the same comments being made via Facebook ‘‘comments’’ about the victim students’ ‘‘Facebook wall’’. The threat was also written on the ‘‘Facebook wall’’. The actually study questions were the same as Study 1. Procedures used were identical to Study 1. 4.2. Results and discussion A total of 36 students were used in the analysis. A repeated measures multivariate analysis of variance (MANOVA) was used to analyze each set of dependent variables (emotions and disruption in daily activity; responses; desired outcomes or goals). The within-subjects factors used were gender of character in bullying scenario (female or male) and medium (electronic or off-line). Gender of the participant was used as a between-subjects variable, in order to assess any gender differences in participant responses. Statistical test assumptions were not violated and no effect due to counterbalancing was found. To ensure that the video clips and Facebook snapshots used in the study had an impact on the adolescents in the intended direction, ratings of negative emotions and disruption in typical activities were examined. Students reported negative emotions and disruption in typical activities equal to or more than usual after watching a bullying scenario. All means were in hypothesized direction. Additionally, almost all of the students’ average ratings were significantly different from how they usually feel if they were the victim in the bullying situation (‘‘same as usual’’ coded as ‘‘3’’) based on a series of one sample t-tests. This suggests the stimuli impacted the s in the intended manner (see Table 6). 4.2.1. Analysis of the impact of Facebook and traditional bullying An omnibus MANOVA analysis indicated a significant interaction between gender of the characters in the scenario (male or female) and emotion (Wilks’ Lambda = .46, F(8,26) = 3.86, p < .01, partial eta squared = .54), indicating that adolescents frequently viewed scenarios with male characters as inducing more negative emotions than scenarios with female characters (for means and standard deviations, see Table 5). Given that past research indicates that OA among males is more likely than among females (Pepler, Jiang, Craig, & Connolly, 2008), it is interesting to note that both male and female students viewed the male OA bullying
Table 5 Means and standard deviations of emotions and disruption in typical activities for Study 2. Item
OA – Male characters Online
Sad Angry Embarrassed Afraid Bad about myself Trusting of othersa Alone or lonely Want to go to schoola Want to go onlinea
OA – Female characters
Off-line
Online
Off-line
M
SD
M
SD
M
SD
M
SD
4.36** 4.47** 4.50** 4.50** 4.33**
0.72 0.70 0.78 0.66 0.72
4.36** 4.58** 4.42** 4.58** 4.22**
0.80 0.60 0.77 0.65 0.80
3.81** 4.39** 3.89** 3.89** 3.81**
0.82 0.65 0.92 1.09 0.92
3.72** 4.36** 4.03** 3.92** 3.78**
0.85 0.93 0.97 1.03 0.87
3.56*
1.28
3.75**
1.27
3.33
1.12
3.64**
1.02
**
4.03
1.03
4.17
**
0.94
3.42
4.28**
0.88
4.36**
0.90
4.33**
0.93
4.06**
1.07
*
*
1.05
3.34
0.91
3.78**
1.05
4.00**
0.89
3.94**
1.09
3.78**
0.87
Note. Scale ranges from ‘‘1: Much less than usual’’ to ‘‘5: Much more than usual’’ to allow for directionality, with ‘‘3: Same as usual’’. a Reverse coded. * p < .05. ** p < .01.
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S. Horner et al. / Computers in Human Behavior 49 (2015) 288–295 Table 6 Repeated measures ANOVAs comparing responses to electronic and traditional bullying, for scenarios with male and female characters. Item
Tell friend Tell adult Do nothing Ask bully to stop Bully the bully Bully others Avoid Facebook Avoid school Joke about it Plot revenge Report to authorities *
Main effect of electronic vs. traditional
Main effect of male characters vs. female characters
Interaction
F(1,35)
Partial eta2
F(1,35)
Partial eta2
F(1,35)
Partial eta2
1.76 5.85* 0.01 3.05
.048 .143 .000 .082
0.89 5.09* 0.16 1.09
.025 .127 .005 .031
1.86 0.00 0.01 0.05
.050 .000 .000 .002
1.00 0.36 2.46
.026 .010 .066
5.00* 0.66 4.14*
.125 .019 .106
0.00 0.55 1.09
.000 .016 .030
3.15 0.64 1.29 0.52
.083 .018 .036 .015
4.53* 8.66* 4.53* 5.08*
.115 .198 .115 .127
1.55 4.58* 0.15 0.02
.042 .116 .004 .001
p < .05.
scenarios as more emotionally upsetting. It is unclear if this higher level of emotional distress is due to an expectation of greater physical harm with male vs. female OA or some other factors. 4.2.2. Analysis of the ways to respond to Facebook and traditional bullying Students were then asked how they would respond if they were the victim in the bullying situation. MANOVA results suggest a three-way interaction between gender of the characters in the scenario (male or female), response, and the adolescent’s gender (Wilks’ Lambda = .45, F(10,23) = 2.85, p < .02, partial eta squared = .55). Follow up ANOVA analyses did not support differences related to participant’s gender. However, additional ANOVA analyses (see Table 6) indicated that participants would be more likely to use the following strategies when a bullying situation involved male characters, regardless of the medium in which the bullying occurred: avoid Facebook, avoid school, report to authorities. In contrast, students reported that they would be more likely to use the following strategies when a bullying situation involved female characters, regardless of the medium in which the bullying occurred: bully the bully, plot revenge. Interestingly, for bullying involving male characters the general preference is for the victim to avoid peers, in contrast, for bullying involving female characters the more likely strategy employed by the victim is to directly retaliate against the bully. One possible explanation for this finding may be due to the differing nature of female vs. male aggression. In particular, females more often employ RA and among high school students this has less potential social cost than OA. Thus, adolescents’ willingness to employ retaliatory strategies when reacting to female bullies may reflect a belief that relationally aggressive behavior is a potentially cost effective option. Further research is needed to explore this greater likelihood for students to utilize retaliation when responding to female bullies. Some notable differences between electronic and traditional bullying did emerge through the open-ended questions. Several students wrote that the ambiguity of threats delivered online were a particular challenge. For example, one adolescent noted that, ‘‘on Facebook, it is much more difficult to read people’s feelings or reactions. If someone was to threaten another person online, it would not be easy to determine the seriousness of the situation like it would be if it happened in person’’. Another stated that threats online are ‘‘worse because you cannot see the person’s reaction and you do not know the tone of how they are saying it’’. These
Table 7 Repeated measures ANOVAs comparing desired outcomes when responding to electronic and traditional bullying, for scenarios with male and female characters. Item
Bullying to stop Get along with bully Keep friends Feel better Maintain reputation *
Main effect of electronic vs. traditional
Main effect of male characters vs. female characters
Interaction
F(1,35)
Partial eta2
F(1,35)
Partial eta2
F(1,35)
Partial eta2
0.47
.013
8.45*
.194
0.05
.001
0.12
.003
2.76
.073
0.00
.000
0.02 0.53 0.00
.000 .016 .000
0.02 0.06 4.53*
.000 .002 .118
0.04 2.06 0.14
.001 .059 .004
p < .05.
comments suggest that although students report both on and offline bullying are similar in the general level of distress, they appreciate of the structural differences in the medium of communication. 4.2.3. Analysis of the desired outcomes in response to Facebook and traditional bullying Students were asked how important different outcomes would be if they were the victim in the bullying situation. MANOVA results reveal an interaction between gender of the characters in the scenario (male or female) and goals the adolescent reports as being important (Wilks’ Lambda = .72, F(4,29) = 2.85, p < .05, partial eta squared = .28), suggesting adolescents view different outcomes of a bullying situation as important when the situation involves males bullying as opposed to females bullying. Follow up ANOVA analyses (see Table 7) indicate that maintaining one’s reputation is most important to adolescents when the scenario involved female characters, as opposed to male characters (online male characters M = 3.20, SD = 1.23 vs. off-line male characters M = 3.17, SD = 1.29; online female characters M = 3.51, SD = 1.10 vs. off-line female characters M = 3.54, SD = 1.04). This finding is consistent with the high importance that adolescent females place on their social reputation. In addition, students indicated that the goal of having the bullying stop would be more important when the bullying situation involved male characters, as opposed to female characters (Bullying to stop: online male characters M = 4.67, SD = .862 vs. off-line male characters M = 4.64, SD = .899; online female characters M = 4.39, SD = .964 vs. off-line female characters M = 4.33, SD = 1.15). It may be that male bullies are perceived as more threatening than female bullies. Further research is needed to understand why this might be the case. 5. General discussion The current studies examined high-school adolescents’ perceptions of electronic and traditional bullying through having students observe hypothetical scenarios, imagine themselves as the victim, and then describe the impact, responses, and goals in resolving the bullying scenarios. As predicted, across all scenarios, students indicated a significant negative impact of bullying situations highlighting the emotions of sadness, anger, embarrassment, fear, and losing trust in others. However, there was a difference found for the strategies most endorsed in response to bullying as related to the gender of the characters involved. When the characters were male, participants of both genders were more likely to endorse strategies of avoidance of the bully. In contrast, when the characters involved (both bully and victim) were female, participants of
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both genders were more likely to endorse strategies of retaliation requiring increased contact between the protagonists. High-school students also indicated the strategy of behavioral avoidance of the context (avoiding school or online activities) where they as the victim might encounter those who had witnessed the bullying. This suggests that the witness or bystander to bullying becomes a negative stimulus in addition to the actual bully. Both on- and off-line, the negative emotional reaction and disruption in typical daily activities demonstrates the high personal cost of peer victimization on adolescents across widely divergent bullying scenarios (e.g., Bonanno & Hymel, 2013; Sticca & Perren, 2013). Overall, across a range of bullying situations (RA or OA, male or female protagonists) there were many similarities in the nature of student reactions to electronic and traditional bullying. As suggested by Bauman and Newman (2012), electronic bullying appears to be a sub-type of the broader category of ‘‘bullying behaviors’’, with concomitant negative outcomes, not a separate and unique phenomenon. This is consistent with preliminary research examining differences between equivalent bullying behaviors on- and off-line among adolescents and young adults (Bauman & Newman, 2013; Sticca & Perren, 2013). It is likely that adolescents experience online and social media activities as an integrated part of their everyday lives. The negative impact of bullying seemed to vary more in response to the type of bullying, overt or relational aggression, or by the gender of the protagonists than by whether the bullying occurred on- vs. off-line. Consistent with the framework of egocentrism and heightened social sensitivity (Buhrmester & Furman, 1987), many of the adolescents’ responses to the open-ended questions in Study 1 indicate the importance of their peer group, and spectators’ potential judgments or opinions. For example, students wrote in response to the relational aggression scenario that it would be particularly hurtful, ‘‘Because all of your friends can see it’’, ‘‘In this situation, it was completely public for all of their friends to see, and they have a whole lot of friends. Also, it can’t be taken back or denied’’, ‘‘Everyone can see everything on Facebook’’, and ‘‘Facebook bullying only hurts your reputation, and maybe your feelings’’. These responses highlight that the victims’ awareness of an audience has a powerful negative impact when being bullied. Given the distinct nature of in-person vs. electronic audiences (e.g., number of witnesses, temporal stability, abstraction) the nature of the embarrassment and distress resulting from bullying in the two mediums needs further exploration. The public nature of the bullying matters and bystanders are not viewed as benign observers but as peers with the potential to judge the victim. Although adolescents in Study 2 emphasized fear in the OA scenarios, adolescents in both studies noted that embarrassment was a powerful emotion connected to all bullying situations. The heightened concern about peers’ viewpoints is highly relevant to adolescents’ experience of being bullied both on- and off-line, and thus needs to be taken into consideration when designing prevention and intervention programs. For example, strengthening adolescents’ positive friendships and building new relationships may help adolescents to diminish the disruptive power of the imaginary audience. One intervention program, described by Slonje, Smith, and Frisén (2013) involves adolescents forming small workgroups at school to deal with specific issues of cyberbullying. This may be a particularly effective intervention because it not only places technology-savvy adolescents at the forefront of problem solving, but also allows adolescents in these groups to form positive peer relationships, thereby improving the school climate. As the current study was an early step in understanding adolescents’ perceptions of electronic and traditional bullying using an experimental design, there are important limitations to be addressed through future research. First, the OA scenario was
reported by adolescents to be both threatening (characteristic of OA) and embarrassing (characteristic of RA; in both Study 1 and Study 2). Given how critical embarrassment is to adolescents, it is unclear if all bullying situations involving OA would be embarrassing, or if this is specific to the scenario chosen, where there was an audience present. Early experimental research on electronic bullying has focused on anger and sadness as responses to bullying, leaving out embarrassment entirely (Pieschl et al., 2013). Thus, further research on the frequency and strength of embarrassment in response to electronic bullying is important. Second, given the rapidly changing format of online communication, some emerging popular forms of communication were not assessed (e.g., Snap Chat, Twitter, Instagram). Third, due to the small sample size in Study 2, it was not possible statistically to compare victim gender (in the bullying scenarios presented) with adolescents’ gender. Prior experimental and self-report studies yield mixed findings with regard to the role of gender in electronic bullying, particularly when directly compared with traditional bullying (e.g., Pieschl et al., 2013; Slonje et al., 2013). Therefore, future research should include more varied bullying scenarios (e.g., a wider range of relationally aggressive behaviors), with the gender of bullies and victims manipulated. This will allow for further exploration of gender differences in responses to a variety of electronic and traditional bullying situations. Overall, given the significant impact, negative emotional reaction, and disruption in typical daily activities of both electronic and traditional bullying (e.g., Bauman & Newman, 2013; Bonanno & Hymel, 2013), adults in adolescents’ lives must recognize the importance of addressing bullying when it occurs both on- and offline. The high acceptance of avoidance strategies in response to bullying is particularly worrisome as it may lead to isolation and reduces the opportunity for positive peer experiences. Given the high degree to which adolescents value the viewpoint of peers, plus their heightened sensitivity to being publically embarrassed, victims may mistakenly avoid those students who could actually be a resource. Initial literature suggests that boys may be more likely to avoid seeking social support when confronted with electronic bullying, and may particularly benefit from interventions designed to combat this tendency (Pieschl et al., 2013). Bystanders and friends are likely to be a critical protective factor if they are able to mitigate the victim’s sense of embarrassment. Future research needs to examine how best to empower adolescents to address the developmental challenges associated with social egocentrism.
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